Research on the Temporal and Spatial Distribution of Marginal Abatement Costs of Carbon Emissions in the Logistics Industry and Its Influencing Factors

Yuping Wu, Bohui Du, Chuanyang Xu (), Shibo Wei, Jinghua Yang and Yipeng Zhao
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Yuping Wu: Research Center of Energy Economic, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China
Bohui Du: Research Center of Energy Economic, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China
Chuanyang Xu: Research Center of Energy Economic, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China
Shibo Wei: Research Center of Energy Economic, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China
Jinghua Yang: Research Center of Energy Economic, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China
Yipeng Zhao: Research Center of Energy Economic, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China

Sustainability, 2025, vol. 17, issue 7, 1-28

Abstract: While existing research has focused on logistics carbon emissions, understanding spatiotemporal emission cost dynamics and drivers remains limited. This study bridges three gaps through methodological advances: (1) Applying the Non-Radial Directional Distance Function (NDDF) to measure Marginal Carbon Abatement Costs (MCAC), overcoming traditional Data Envelopment Analysis (DEA) model’s proportional adjustment constraints for provincial heterogeneity; (2) Pioneering dual-dimensional MCAC analysis integrating temporal trends (2013–2022) with spatial autocorrelation; and (3) Developing a spatial Durbin error model with time-fixed effects capturing direct/indirect impacts of innovation and infrastructure. Based on provincial data from 2013–2022, our findings demonstrate a U-shaped temporal trajectory of MCAC with the index fluctuating between 0.3483 and 0.4655, alongside significant spatial heterogeneity following an Eastern > Central > Northeastern > Western pattern. The identification of persistent high-high/low-low clusters through local Moran’s I analysis provides new evidence of spatial dependence in emission reduction costs, with these polarized clusters consistently comprising 70% of Chinese cities throughout the study period. Notably, the spatial econometric results reveal that foreign investment and logistics infrastructure exert competitive spillover effects, paradoxically increasing neighboring regions’ MCAC, a previously undocumented phenomenon in sustainability literature. These methodological advancements and empirical insights establish a novel framework for spatial cost allocation in emission reduction planning.

Keywords: logistics industry; marginal carbon abatement cost; DEA; spatial effects (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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